Takashi Washio
Causal Inference & Discovery · 2000–2018
A researcher in the Science corpus: 6 papers; trusts 19 researchers and is trusted by 32 researchers here, as inferred from the citation graph.
Subfields
- Causal Inference & Discovery — 26 citations into it; #268 of 364 by trust here, #350 by citations
- Artificial Intelligence — 25 citations into it; #25,241 of 35,345 by trust here, #31,361 by citations
- Signal Processing — 15 citations into it; #4,532 of 7,572 by trust here, #5,340 by citations
- Statistics and Probability — 14 citations into it; #9,510 of 12,932 by trust here, #10,275 by citations
- Probabilistic & Bayesian Methods — 11 citations into it
- Algorithms & Complexity — 8 citations into it
- Analytical Chemistry — 7 citations into it
- Control and Systems Engineering — 7 citations into it
Whom Takashi Washio trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Rakesh Agrawal
- Dominik Janzing
- Aapo Hyvärinen
- Rayadurgam Srikant
- Bernhard Schölkopf
- Jan Peters
- Vladimir Naumovich Vapni
- Kun Zhang
- Mohammed J. Zaki
- Patrik O. Hoyer
Who trusts Takashi Washio overall
- Michihiro Kuramochi
- Xifeng Yan
- Jiawei Han
- Chuntao Jiang
- George Karypis
- Yuanyuan Tian
- Holger Fröhlich
- Jun Huan
- Till Quack
- Bernhard Schölkopf
Papers from Takashi Washio's perspective
Ordered by how strongly the researchers Takashi Washio trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- The Nature of Statistical Learning Theory
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Regression Shrinkage and Selection via the Lasso
- GENERATIVE ADVERSARIAL NETS
Their papers
- Error asymmetry in causal and anticausal regression (2016) — 13 citations
- An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data (2000) — 1,185 citations
- Complete Mining of Frequent Patterns from Graphs: Mining Graph Data (2003) — 317 citations
- State of the art of graph-based data mining (2003) — 512 citations
- Cause-Effect Inference by Comparing Regression Errors (2018) — 93 citations
- DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model (2011) — 674 citations